This invention relates to surface measurement, particularly of patterned surfaces to analyze surface characteristics of a patterned workpiece under study.
In processes employed today in the manufacture of solid state devices from wafers, complex processes are followed which frequently leave the wafer with certain surface (and subsurface) features, residues and characteristics. For example, in making integrated circuits and chips from semiconductor wafers and for micro-mechanical apparatus, a large number of manufacturing steps are employed to produce structural features such as bridges, cavities, interconnects, vias, etc. and may include, for example, spin-on photoresists, photoresist processing, etching, deposition of films (both dielectric and conducting), ion implantation, chemical mechanical polishing (CMP) and other polishing steps, which may, with other processes, all be included in the treatment of and creation of an ultimate device. Similarly, processes are employed in manufacture of magnetic hard disks and magnetic read/write heads. Aluminum oxide/titanium carbide (AlTiC) wafers, used in the thin film magnetic head industry and other semiconductor materials such as gallium arsenide, used for specialized devices, are processed in a similar manner which can be expected to leave surface and sub-surface effects which can significantly effect the ultimate product. For the purposes of this description, xe2x80x9csurfacexe2x80x9d includes not only the outer extreme of a layer or substrate but also the optically accessible interface between adjacent layers.
It is known in prior art to acquire spatial images of surface features of wafers containing numerous device units (xe2x80x9cdiexe2x80x9d), to evaluate these for consistency of structure and to discover deficient die, and similarly to compare nominally identical wafers and components thereon. A variety of apparatus is known for this purpose, with a unifying characteristic that an image of the surface under inspection is acquired. This image is a true mapping of a spatial image of a tangible two dimensional (albeit, microscopic) surface of interest. In manufacture of semiconductor die and like articles, a large number of identical structures are formed on a common substrate, or wafer and the efficacy of the processing steps becomes evident in the percentage (xe2x80x9cyieldxe2x80x9d) of acceptable device units or equivalent articles which are finally realized on conclusion of the processing steps. Individual die, and the wafer as a whole present a discretely patterned surface. Defects which appear at intermediate stages of the processing are determinative of the upper limit to yield and thus there is an advantage in evaluating die at various stages of manufacture. In evaluating the physical character of the surfaces for comparison with like surfaces or for comparison with some reference surface, the prior art requires image processing to locate the corresponding spatial features by pattern recognition procedures, a slow, cumbersome (and error prone) process in the context of the duration of process steps. Yet, this is the type of processing in use today.
As technology develops in the semiconductor manufacturing fields, the manufacturers are forced to tighter process tolerances and are compelled to use process controls capable of analyzing key factors to assure satisfactory results and to control and increase yields and device performance. This is a result of defects becoming smaller in size as well as new defect sources from material changes and process variations require more responsive instrumentation and techniques to inspect and analyze manufactured products for anomalies and defects.
Instrumentation exists that can illuminate the surface with controlled optical polarization states and inspect and analyze for film thickness and defects. Many such instruments have more than one concurrent data channel, e.g., sensitivity to scattered light, polarization specific reflectance, phase differences at selected angles of incidence, selectable narrowly wavelength dependance and phase difference information from specularly reflected light derived from a stabilized source. These channels may typically have a known relationship for their collected data as a function of the sample""s properties such as, the shape, composition and/or thickness of each layer of a stack of films or the composition and size of particles at the interface.
Polarization tools such as a surface reflectance analyzer (SRA) measure a combination of scattering, reflectance, polarization ratio, and phase differences. These measurements can be made as a function of the angle of incidence, wavelength, and type of incident polarization. Any combination of these measurements can be used for multidimensional histogram analysis. In this invention, suface reflectance and optical reflectance analysis are terms intended as generic representation of these test processes and devices as well as equivalent techniques and instruments.
An example of such prior instrumentation is contained in U.S. Pat. No. 6,134,011, commonly assigned, and incorporated for reference herein. Such instrumentation is available from HDI Instrumentation located in Santa Clara, Calif. A preferred such unit is identified as an SRA Instrument. The deviations that were addressed in prior art applications included variations in uniformity or constant thickness, etc. for a workpiece of a nominally homogeneous external surface. The processes that have existed, principally address relatively slowly varying observables. Prior instrumentation however, has not heretofore been addressed to the problem of enabling surface determinations as to investigate or evaluate or compare discrete, systematic variations on surfaces comprising patterns on samples or to the concern that can arise in the semiconductor manufacturing field of determining where defects exist.
This invention is concerned with rapid, concurrent measurement techniques where the observeable data changes rapidly in respect to spatial variables, which is typical for patterned surfaces. The invention describes a way to analyze the data streams from several related data channels directed toward comparative examination of patterned surfaces using a multi-dimensional histogram. In its simplest form, data from two channels are combined in a two dimensional (2D) histogram. Multi-dimensional histogram analysis has, been used to correlate medical images (see U.S. Pat. No. 5,509,084), to perform color separation (see U.S. Pat. No. 5,432,545), or in measuring thin film properties in magnetic recording disks (see Vurens and Klein SPIE Vol 3619, 1999, page 27; Klein and Vurens, SPIE Vol 3619, 1999, page 18; Meeks et al. J. Tribology 117; 1995, page 112). In general higher dimensional histograms can also be used (e.g., 3D or 4D), or multiple correlated 2D histograms may be used for data analysis. The prior art may be generally characterized as employing multidimensional histograms for the purpose of examining non-uniformities of slowly varying characteristics in a single workpiece under investigation.
A multi-dimensional histogram analysis has unique advantages in dealing with data obtained from scanning patterned surface workpieces such as device bearing substrates, for which semiconductor wafers serve as an example. For the purposes of this work, xe2x80x9cpatternxe2x80x9d is meant to convey systematically ordered features, spatial and/or compositional, which exhibit substantial discontinuities or posses relatively large spatial derivatives. As described these wafers typically have complex patterns of multiple and overlapping films on their surfaces forming a microscopic three dimensional spatial topology e.g., die, which is repeated over the wafer area. Typically, one is interested in the properties of certain regions that contain a unique film pattern on the sample. Currently, in order to study these particular regions, software is used that automatically compares different (nominally identical) areas using programs developed for pattern recognition of spatially imaged regions. Sometimes this approach is used to compare a region of interest with a comparable region nearby on the surface of the same, or disposed on a nominally identical wafer. This is sometimes referred to as die-to-die comparison. The comparison may be directed from a die under examination to another reference, such as a specified model or master or simulation. This type of software for recognition and comparison of spatial images is complex, slow and prone to error. For certain applications the proposed histogram analysis of the present invention can be used to analyze uniformity across patterned surfaces quickly and accurately without the use of such spatial imaging, spatial image recognition and procedures to make spatial image comparisons. For comparison of workpieces, whether patterned or nominally uniform, the differences in non-spatial multi-dimensional histograms provides rapid and reliable detection and determination of the aberrant workpiece or segment thereof.
The purposes of this invention are achieved by collecting various data streams from an instrument optically scanning a patterned surface being examined. This can be done by simultaneously detecting correlated optical data streams representing, for example, reflectance and phase difference of controlled and resolved polarization states. The acquired data streams may be stored in the form of sequential correlated records or processed for storage and use as multi-dimensional histograms. In the latter case, the sequential records may be sorted to form multi-dimensional histograms of desired characteristics. Importantly, in the preferred usage, the histogram retains a direct relationship to the original data sets. This data is non-spatial in character; consequently, two such histograms of nominally identical structures may be directly compared on a cell by cell basis in the non-spatial domain thus avoiding reliance upon pattern recognition and pattern alignment. This permits use of the histogram technique to distinguish areas with large differences as well as to permit highlighting areas for smaller variations and enables locating differences for nominally corresponding patterns.